2. Predictability of asset returns∗
Deterministic and Random Walk approach
∗ MA6622,
Ernesto Mordecki, CityU, HK, 2006.
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Question:
Can we predict future values of an asset?
More precisely:
How to model the time evolution of prices
of financial instruments, as stocks, indexes,
commodities, etc.
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We have different approachs:
• Deterministic Approach (YES, we can predict)
• Stochastic Approach:
– Unpredictable (random walk - martingale, NO, we can not predict)
– Predictable (time series, YES, we can
statistically predict)
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2a. Deterministic approach
Consists in the assumption that future prices,
future demand, etc. are deterministic, i.e.
precisely known in advance. The question is
then to make the financial decisions in order
to maximize the gain of investors.
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For instance, in order to decide whether to
invest in a project that costs I0, one computes the Net Present Value (NPV) of this
investment as
n
X
St
NP V =
− I0
t
(1
+
k)
t=1
where St is the expected income of year t,
I0 the initial investment, k is the discount
rate, and n is the duration (in years) of the
project.
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2b. Stochastic Approach
Initiated by Markowitz (1952) who considered the optimization of investment decisions
under uncertainty, the so called mean-variance
analysis, with the main consequence of the
advantages of diversification in order to reduce the risk, measured here as the variance
of the expected return.
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A second step was the Capital Asset Pricing Model (CAPM) by Sharpe (1964), constructing an optimal invesmentment policy
in a portfolio with several different assets.
A third step was the Arbitrage pricing theory
(APT) of Ross (1976), being a generalization of the latter.
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In reference to the risks, we distinguish
• Unsystematic risks that can be reduced,
for instance, by diversification,
• Systematic risks due to the stochastic
nature of the models.
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2c. Unpredictability of asset returns:
• Efficient markets
• Random walk hypothesis
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An efficient market has:
• instantaneous corrections of prices withouth posibility of buying low to sell high
(i.e. we do not have arbitrage opportunities).
• All dealers interpret price movements in
the same way
• The participants are homogeneous and
behave rationally
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This three postulates are consistent with the
Random walk hypothesis, that proposes to
model prices of an asset {Sn} as
Sn = exp(h1 + · · · + hn),
n ≥ 1,
where h1, h2, . . . is a sequence of independent random variables, defined in a probability space (Ω, F , P).
In other words, the random variables
Sn
S
,...
h1 = ln 1 , . . . , hn = ln
S0
Sn−1
are independent.
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Several empirical studies confirm this hypothesis in different situations (stock markets,
commodity prices) but of course, one should
be cautious about the universality of this
model.
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In continuos time, Samuelson (1965) and
Black and Scholes (1973) and Merton (1973)
proposed the model
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St = S0 exp σWt + (µ − σ /2)t ,
for t ≥ 0, where
• {Wt} a Wiener process defined on (Ω, F , P),
• σ is the volatility,
• µ is the expected return.
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